Oil and gas exploration, appraisal and production is becoming increasingly difficult and automation of drilling, completion, stimulation and production operations is being explored as a means to improve economics and safety. Past automation attempts have achieved varying degrees of success, and a few are now deployed in the field. These recent developments are very encouraging. However, there still remain significant challenges that need to be overcome before broader adoption of automation in the oil and gas industry is achieved.
Each well that is drilled, completed, stimulated and produced is unique and sensors, actuators, and other rig equipment vary in type, number, performance and quality from one rig to the next. This implies that automation and control algorithms (especially ones that can have safety and high cost ramifications on failure) have to be reviewed and signed off for each well constructed. Current algorithms (except for the simplest ones) require tight control on the hardware for execution, and require significant expertise for adaptation from one rig to another.
A well drilled today generally has four primary stakeholders: the operator, the service provider(s), the drilling contractor, and the equipment manufacturer(s). An automation solution usually requires input from all these parties. Each of them holds data critical to a complete automation solution. More often than not, these stakeholders are hesitant to share data due to competing interests. There is a general consensus that the operator is the stakeholder who holds most authority in this scenario and is best suited to play the role of a data integrator/automation supervisor. But integrating all the data together (when the operator does get access) and devising a control algorithm in a short time period of time is a challenge.
Drilling contractors are often very cautious when it comes to automated algorithms. There are several reasons for this. A first concern is safety: control algorithms provided by service providers and operators are often black box/proprietary, and rig contractors are hesitant to hook them up to their rig systems because of potentially harmful (to people, equipment, etc.) unintended consequences/failures. Secondly, it is often unclear what the value-proposition is for the rig contractor. The potential benefits to an operator or service provider may be evident, whereas, the rig contractor may see only downside risks by adopting automated routines. Both of these concerns need to be addressed to achieve the buy-in of the rig contractor. Hence, making the control algorithm transparent and intuitive for the senior rig contactor representatives at the rig site (e.g., tool pusher, driller) goes a long way to addressing the black box concern.
Data quality in the oil and gas industry is generally not good enough to reliably implement automated control algorithms. Many who have implemented automation solutions in the past recommend improving rig instrumentation. While this is a desirable goal, it is generally not an economically viable solution on a broad level. The current generation of automation algorithms however are not capable of independently handling uncertainties in sensed data generated by current rig instrumentation, presenting a significant hurdle to the adoption and further development of automated solutions.